Have you heard Michael Jackson’s cover of The Weeknd’s “I Feel it Coming?”
If you think you did, you’re just one of many who has been fooled by AI-generated content in the last year.
MJ passed away seven years before the Canadian singer even released the chart-topping collaboration with Daft Punk—this cover is an impossibility.
But with the exploding power of generative AI, musicians can perform beyond the grave, artists who developed genre-bending styles can be mimicked to a T, and the words and tone of the world’s most famous writers can be replicated with the press of a button.
Music, art, and literature aren’t the only industries being impacted by this new technology; generative AI is also changing marketing as we know it.
This exploding technology is marketers’ newest collaborator, enabling them to generate content, develop scalable marketing strategies, and optimize for performance at every level of their campaigns, ultimately driving revenue for their companies.
So, what exactly is generative AI?
Generative AI is marketers’ newest collaborator
Generative AI is a type of artificial intelligence that processes large language models to create content like copy, videos, audio, images, and other net-new content from scratch using human inputs.
This makes it gold for marketers when it comes to their day-to-day activities.
Generative AI brings massive potential for innovation, and marketers who embrace it will become more performative, efficient, and productive.
And if you don’t get on board with the generative AI craze, your competitors will—according to Gartner, 30% of outbound messages from large organizations will be created by generative AI by 2025.
So, how can you start implementing generative AI today?
I sat down with Stagwell Marketing Cloud’s Chief Technology Officer Mansoor Basha to get a better pulse on the different ways marketers should think about leveraging gen AI on their teams. Basha gave me four key areas where companies can start their generative AI journey: content generation, processing and activation, analysis, and reporting.
First, generative AI can help collate, curate, and gather information. Basha emphasizes that gen AI is a partner for finding resources, consolidating research, and packaging information before executing an ask. In order to get a good output from gen AI, you need strong inputs.
Up next, Basha emphasized the importance of generative AI in the creation of assets—and this isn’t just limited to copy. “Generative AI is being used for images, for videos, and for other things as well. So, we’re not just copyediting, but also carrying out image editing and image generation.”
After launching your AI-generated content, it’s time to see how it performed.
This is where analysis comes in. “Once the results are executed, bring back the information, and process it again: Understand what is going on here. For example, what were the highlights? Why did that happen? Ask the model the right kinds of qualitative and quantitative questions to get the answers.”
As for the final area where gen AI can lend a helping hand, Basha highlighted activities such as “creating a chart” or “creating summaries”…essentially, reporting.
“People can get annoyed while working in marketing because there’s a lot of drudgery work. For example, if you are asked to fix the font on a PowerPoint slide—do you really want to do that?” said Basha.
With generative AI, people “can focus on creativity versus mundane tasks,” says Basha.
But how do these different focus areas show up more concretely in the modern marketer’s day to day?
Let’s dive into five use cases you can implement now.
As we’ve discussed, content generation is one major area where generative AI can pack a punch for marketers. It’s also probably the topic you’ve seen taking up endless LinkedIn feed real estate as thought leaders weigh in on the benefits and pitfalls of gen AI for content creation.
Struggling with the blank page problem? Creative brainstorms stalling? Need to come up with ten headlines fast?
Generative AI can help with all of that.
Generative AI assists marketers in creating copy. This could apply to content that appears anywhere, from blogs to social media, landing pages and outreach emails. As that famous saying goes, “Behind every great blog post is a great AI chatbot.”
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But seriously, tools like Jasper, Braze, Writer, and Copy.ai are putting writing assistants in every marketer’s pocket—and investments in the space aren’t decreasing any time soon. According to data from Pitchbook, investors funneled a whopping $11.2 billion into generative AI in Q1 of 2023.
More specialized content writing tools are also starting to hit the market. PRophet, a SaaS platform that helps PR professionals surface and connect with relevant journalists and podcasts, recently launched their gen AI capability, Taylor.
Taylor can help PR professionals write press releases, pitches, and social media posts for their news.
Tools like this are changing the way marketers write their first draft, and the ability to indicate the tone you’re looking to for, the length of copy you want, and what channel you’re publishing for makes gen AI copywriting software table stakes for marketers.
Generative AI is the ultimate pattern identifier, and this can help with content optimization efforts across the board. Marketers can identify trending keywords, improve keyword density, or learn more about what makes content go viral using generative AI. Not to mention the potential for creative asset optimization.
Team Whistle, a sports and entertainment company that distributes content through various social media platforms, experimented with generating keywords, metadata, and hashtags for their recent content using gen AI. A YouTube video they published around four months ago has received over 425,000 views so far. This is over three times the number of views many of the videos published around the same time received.
According to Team Whistle’s EVP of content Noah Weissman, the company makes 30 to 50 TikTok videos a day, and generative AI helps the company determine which keywords would make the videos most successful.
And this doesn’t just apply to social virality, it can also be used for Search Engine Optimization, or SEO.
Generative AI can help marketers automate internal linking processes, optimize content structure and headings to Google’s likings, summarize research to make the writing process more seamless, and generate strategic headlines in line with search best practices.
Lastly, generative AI is making a splash in the creative optimization world. Tools like SmartAssets are hitting the market to reduce digital waste and increase ad efficacy.
SmartAssets uses AI to analyze a brand’s performance data and offer tweaks to ad creative (think turning a dress from blue to green in your ad image) to ensure that ads are as successful as possible without the cost and labor that goes into testing.
Up next, generative AI can be a critical partner for companies who need to translate marketing assets into different languages. While AI might not get the translation 100% right yet—or 100% in line with different cultural norms and hard-to-translate puns—it’s a great place to start.
According to Lindsay Hong, the Chief Operating Officer of multilingual translation agency Locaria, “the key to successful adoption of automation, particularly AI, is the ability to take measured risks to test and learn about the efficacy of any given model for your specific content needs.”
“The key to successful adoption of automation, particularly AI, is the ability to take measured risks to test and learn about the efficacy of any given model for your specific content needs.” —Lindsay Hong, Chief Operating Officer of Locaria and Co-Founder of SmartAssets.
Hong mentioned that “foreign language copy is arguably much harder for internal teams to have a view on than the visual elements of marketing assets.” She said that “marketers should seek out agencies that have an AI content strategy and want to partner to identify the right model together with the brand.”
Generative AI can also be used to help marketers hone their overall strategy in a few different ways.
First of all, the amount of automation that can be done by gen AI creates significant time savings. (Hubspot found that marketers save an average of 3 hours and 10 minutes to finish a singular content segment when creating with gen AI.) This leaves marketers with more time to think strategically instead of always rushing from one mission critical task to the next.
Generative AI is also a great brainstorming partner: With the right inputs, a tool like ChatGPT could scour the internet’s sources on marketing strategy and summarize result-driving programs to help guide your thinking or inspire ideation. Don’t take information provided by ChatGPT at face value though—always think critically about the results it provides and fact check when necessary.
Lastly, generative AI’s impact on strategy can be seen through the value it creates.
AI can help boost revenue for companies by improving their processes “so they can differentiate themselves in the market,” says Basha. This allows marketers to “focus on things that are really important and then go back to the customer and say ‘I’m doing more value-added work for you.’”
Bahsa added that a company’s capital expenditure can also go down as with generative AI, you can “remove a lot of other tools which you are spending on.” Keeping an eye on software spend and process improvements is critical for marketing leaders.
In the same way generative AI can “write” a 10-page essay on that Victorian novel you “read” and “loved,” it can also generate images and videos.
Like copy generation, creating images with generative AI requires human inputs. Anything you can dream, applications like DALL-E can make digitally tangible.
Chicken eating cheetos on the moon? ✅
Lebron James in the style of Leonardo da Vinci? ✅
You get the picture.
And condiment brand Heinz took a first stab at deploying generative AI image tools in their recent campaign.
Heinz asked DALL-E 2 to create an image of ketchup. And ketchup in a swimming pool. And ketchup in outer space. And ketchup in the style of street art.
They found that something stayed relatively consistent between every image: The shape of the bottle and the label look remarkably similar to Heinz’s ubiquitous branding. Even following absurd, fan-generated prompts, DALL-E 2 showed an outline of a Heinz ketchup bottle with any search that included the word ketchup.
For this AI-generated campaign, Heinz concluded: “Just like humans, A.I. prefers Heinz.”
If it’s not clear yet, let me sum this all up: Generative AI is an extremely powerful technology that will continue to make an impact across industries.
And that comes with some trepidation from the marketers and designers who make a living writing copy that converts or creating brand-defining assets. Reasonably so! Research from Goldman Sachs estimates that 26% of work in design, the arts, and other creative industries could be taken over by AI.
But at the end of the day, generative AI will not replace humans, as humans possess empathy and strategic insight. The success of generative AI only comes from the quality of human input.
Pegah Yazd, Stagwell Marketing Cloud’s Senior Art Director told me that she doesn’t think that we should expect for AI to fully take over jobs like writing TV scripts or making artwork.
But at the end of the day, generative AI will not replace humans, as humans possess empathy and strategic insight. The success of generative AI only comes from the quality of human input.
Yazd added that there is “a lot of hope with certain events such as the writer strike and organized labor to protect the work of creatives and to protect their role in society.”
Human talent isn’t going to be usurped by AI any time soon: “Humans need art. We need culture to live,” said Yazd.
Yazd herself has taken advantage of AI during her own career as a designer: “I think it’s extremely helpful for me and my process now,” said Yazd. “I’ve already kind of integrated it into my creative workflow, especially when it comes to generating mood boards.”
The best thing marketers can do is start using generative AI to their advantage and learn how to make it a friend, not a foe.
In order to use generative AI at scale, AI safety training will need to become mandatory at every business.
Without human oversight, robust security standards, and employee training, bringing non-enterprise-grade generative AI tools into businesses could compromise security. Getting every team on board with how to responsibly use AI should be a priority for any business experimenting with this technology.
As Hong said, “The potential for scaling global content more easily with AI is huge, but it’s a journey, not a binary decision.”
